Exploration and production document content and metadata scanner

A system comprising:

• memory;
• and a processor for executing computer readable code configured to perform operations comprising:
• obtaining, for a plurality of oilfield document content classes, a training set comprising a plurality of documents;
• calculating an inverse document frequency from the plurality of documents in the training set;
• calculating term frequency inverse document frequency (TF-IDF) of terms in the training data set to generate a plurality of TF-IDF vector results related to a plurality of document content classes;
• training the document content type classification model using the plurality of TF-IDF vector results;
• extracting, from a file comprising an unstructured oilfield document, a plurality of terms, calculating TF-IDF of the plurality of terms to generate an input vector, executing a document content classification model on the input vector to generate a document content classification of unstructured oilfield document, extracting table information from a table in the unstructured oilfield document, and storing, with the file in storage, the document content classification and the table information.

A non-transitory computer readable medium comprising instructions that, when executed by a computer processor, perform operations comprising:

• obtaining, for a plurality of oilfield document content classes, a training set comprising a plurality of documents;
• calculating an inverse document frequency from the plurality of documents in the training set;
• calculating term frequency inverse document frequency (TF-IDF) of terms in the training data set to generate a plurality of TF-IDF vector results related to a plurality of document content classes;
• training the document content type classification model using the plurality of TF-IDF vector results;
• extracting, from a file comprising an unstructured oilfield document, a plurality of terms;
• calculating TF-IDF of the plurality of terms to generate an input vector;
• executing a document content classification model on the input vector to generate a document content classification of unstructured oilfield document;
• extracting table information from a table in the unstructured oilfield document;
• and storing, with the file in storage, the document content classification and the table information.